The invention relates to a system for monitoring technical processes, machines, installations and apparatuses. If changes in the normal condition are detected promptly, major instances of damage can be avoided by promptly performing corrective actions before major instances of damage associated with prolonged downtimes occur. Changes in machines, apparatuses and installations are caused by wear, corrosion, deposits, plugging, contamination, and nonspecifically occurring operational malfunctions.
First approaches to machine condition monitoring with an eye to crash prevention and condition-oriented maintenance are based on complicated mathematical calculations preferably based on neuronal networks. They have the disadvantage that a very great cost expenditure is occasioned because the application in question must be trained. The results obtained are rather meager. Other methods also address only partial aspects and have not met with total success.
The difficulty in assessing a machine condition results from the following circumstances. Small changes in the temperature values of bearing positions, for example, are significant for the degree of wearing-out of the bearings. The temperature values, however, are subject to a number of service-associated influences. The temperature values are affected by the rotation speed, the radial force and the ambient temperature. It is therefore not possible, according to the existing art, to track small changes, because service-associated fluctuations in the measured values are larger than the small changes attributable to bearing wear.